code: def _compile_model(
      self,
      model: Union[Module, GraphModule],
      network_parameters: ModelParams,
  ) -> Any:
      dynamic = False
      if network_parameters.dynamic_info is not None:
          dynamic = True
      return torch.compile(model, dynamic=dynamic)
  
file_path: nebuly/optimization/nebullvm/nebullvm/operations/optimizations/compilers/torch_dynamo.py
imports: from typing import Union, Any
  from nebullvm.core.models import ModelParams, QuantizationType
  from nebullvm.operations.optimizations.compilers.base import Compiler
  from nebullvm.optional_modules.torch import torch, Module, GraphModule
  from nebullvm.tools.data import DataManager
  from nebullvm.tools.transformations import MultiStageTransformation
label_desc: Use image node_id 2 for calling the TorchDynamoCompiler obj's underlying member method code with example usage: obj._compile_model(model, network_parameters) and returns: torch